Investigating the capabilities of aerial digital images of UltraCam-D Camera to identify Zizyphus spina chrisiti and Astragalus spp. in semi-arid regions (Case study: Poshtkuh, Bushehr province)

Document Type : Research Paper

Authors

1 Ph.D. Candidate, Forestry, Faculty of Natural Resources, Sari Agricultural Sciences and Natural Resource University, Sari & Research Expert, Forest and Rangeland Division, Bushehr Agricultural and Natural Resources Research and Education Center, AREEO, Bushehr, Iran.

2 Prof., Department of Forestry, Faculty of Natural Resources, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.

3 Prof., Department of Forestry, Faculty of Forest Sciences, Gorgan Agricultural Sciences and Natural Resources University, Gorgan, Iran.

10.29252/aridbiom.2020.1817

Abstract

The present research was carried out with the aim of identification and separation of zizyphus spina christi and Astragalus sp. species as well as providing a distribution map of the mentioned species using UltraCam-D digital images in a part of the mountainous Bushehr province. Different techniques of enhancement were applied including Texture Analysis, Principal Component Analysis (PCA) and ratio of the bands. Five band groups were selected including main bands, band set obtained from image texture analysis, main bands along with indices and the first obtained band from PCA and a collection of the best bands obtained from OIF. The training samples were produced through field method. Then, 70% of the samples were applied for various classifier pixel-based algorithms including, Mahalanobis Distance classification, Maximum Likelihood classification, Neural Net Classification, Support Vector Machine (SVM) and Random Forest classification. Verification of the results was carried out using 30% of actual ground samples. Results of assesment of images classified by various algorithm showed that the maximum overall accuracy (85.69%) and kappa coefficient (0.72) in separating the three classes of zizyphus spina christi, Astragalus sp. and soil from the other mixed vegetation cover are for classification by Mahalanobis Distance Classification algorithm applied on group of four main band, PC1, NDVI and SAVI. In general, the results of classification by pixel-based method represent proper efficiency of UltraCam-D digital data for identification and separation of desert regions species particularly zizyphus spina christi from Astragalus sp and shrub species.

Keywords

References

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Journal of Arid Biome
Volume 9, Issue 2
March 2020
Pages 71-84

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